
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import plotly.express as px

data = pd.read_csv("unemployment.csv")
print(data.head())

           Region         Date  Frequency   Estimated Unemployment Rate (%)  \
0  Andhra Pradesh   31-01-2020          M                              5.48   
1  Andhra Pradesh   29-02-2020          M                              5.83   
2  Andhra Pradesh   31-03-2020          M                              5.79   
3  Andhra Pradesh   30-04-2020          M                             20.51   
4  Andhra Pradesh   31-05-2020          M                             17.43   

    Estimated Employed   Estimated Labour Participation Rate (%) Region.1  \
0             16635535                                     41.02    South   
1             16545652                                     40.90    South   
2             15881197                                     39.18    South   
3             11336911                                     33.10    South   
4             12988845                                     36.46    South   

   longitude  latitude  
0    15.9129     79.74  
1    15.9129     79.74  
2    15.9129     79.74  
3    15.9129     79.74  
4    15.9129     79.74


print(data.isnull().sum())

Region                                      0
Date                                        0
 Frequency                                  0
 Estimated Unemployment Rate (%)            0
 Estimated Employed                         0
 Estimated Labour Participation Rate (%)    0
Region.1                                    0
longitude                                   0
latitude                                    0
dtype: int64


data.columns= ["States","Date","Frequency",
               "Estimated Unemployment Rate",
               "Estimated Employed",
               "Estimated Labour Participation Rate",
               "Region","longitude","latitude"]


plt.style.use('seaborn-whitegrid')
plt.figure(figsize=(12, 10))
sns.heatmap(data.corr())
plt.show()

C:\Users\sarosh sheikh\AppData\Local\Temp\ipykernel_5364\420329394.py:1: MatplotlibDeprecationWarning: The seaborn styles shipped by Matplotlib are deprecated since 3.6, as they no longer correspond to the styles shipped by seaborn. However, they will remain available as 'seaborn-v0_8-<style>'. Alternatively, directly use the seaborn API instead.
  plt.style.use('seaborn-whitegrid')
C:\Users\sarosh sheikh\AppData\Local\Temp\ipykernel_5364\420329394.py:3: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.
  sns.heatmap(data.corr())


data.columns= ["States","Date","Frequency",
               "Estimated Unemployment Rate","Estimated Employed",
               "Estimated Labour Participation Rate","Region",
               "longitude","latitude"]
plt.title("Indian Unemployment")
sns.histplot(x="Estimated Employed", hue="Region", data=data)
plt.show()


plt.figure(figsize=(12, 10))
plt.title("Indian Unemployment")
sns.histplot(x="Estimated Unemployment Rate", hue="Region", data=data)
plt.show()


unemploment = data[["States", "Region", "Estimated Unemployment Rate"]]
figure = px.sunburst(unemploment, path=["Region", "States"], 
                     values="Estimated Unemployment Rate", 
                     width=700, height=700, color_continuous_scale="RdY1Gn", 
                     title="Unemployment Rate in India")
figure.show()